# Copyright 2023 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
from tests.mark_utils import arg_mark
import numpy as np
import pytest
import mindspore as ms
import mindspore.nn as nn
from mindspore import Tensor
from mindspore import ops
from mindspore.common.api import _pynative_executor


class Net(nn.Cell):
    def __init__(self, dim=0, start=None, end=None, step=1):
        super(Net, self).__init__()
        self.dim = dim
        self.start = start
        self.end = end
        self.step = step

    def construct(self, input_x, src):
        return ops.slice_scatter(input_x, src, self.dim, self.start, self.end, self.step)


@arg_mark(plat_marks=['platform_ascend', 'platform_gpu', 'cpu_linux', 'cpu_windows', 'cpu_macos'], level_mark='level1',
          card_mark='onecard', essential_mark='unessential')
@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
def test_ops_slice_scatter(mode):
    """
    Feature: ops.slice_scatter
    Description: Verify the result of slice_scatter
    Expectation: success
    """
    ms.set_context(mode=mode)
    x = Tensor([[[0, 1, 2],
                 [3, 4, 5],
                 [6, 7, 8]],
                [[9, 10, 11],
                 [12, 13, 14],
                 [15, 16, 17]]], ms.float32)
    y = Tensor([[[28, 29, 30]],
                [[31, 32, 33]]], ms.float32)
    net = Net(1, 0, 1, 1)
    output = net(x, y)
    expect_output = [[[28., 29., 30.],
                      [3., 4., 5.],
                      [6., 7., 8.]],
                     [[31., 32., 33.],
                      [12., 13., 14.],
                      [15., 16., 17.]]]
    assert np.allclose(output.asnumpy(), expect_output)


@arg_mark(plat_marks=['platform_ascend', 'platform_gpu', 'cpu_linux', 'cpu_windows', 'cpu_macos'], level_mark='level1',
          card_mark='onecard', essential_mark='unessential')
@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
def test_ops_slice_scatter_error(mode):
    """
    Feature: ops.slice_scatter error
    Description: Verify the error of slice_scatter
    Expectation: success
    """
    ms.set_context(mode=mode)
    x = Tensor([[[0, 1, 2],
                 [3, 4, 5],
                 [6, 7, 8]],
                [[9, 10, 11],
                 [12, 13, 14],
                 [15, 16, 17]]], ms.float32)
    y = Tensor([[28, 29, 30]], ms.float32)
    net = Net(1, 1, 1, 1)
    with pytest.raises(ValueError):
        net(x, y)
        _pynative_executor.sync()

    with pytest.raises(TypeError):
        net(1., 2)
        _pynative_executor.sync()


@arg_mark(plat_marks=['platform_ascend', 'platform_gpu', 'cpu_linux', 'cpu_windows', 'cpu_macos'], level_mark='level1',
          card_mark='onecard', essential_mark='unessential')
@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
def test_ops_slice_scatter_neg_end(mode):
    """
    Feature: ops.slice_scatter
    Description: Verify the result of slice_scatter with neg end.
    Expectation: success
    """
    ms.set_context(mode=mode)
    x = Tensor([[[[0, 1, 2],
                  [3, 4, 5],
                  [6, 7, 8]],
                 [[9, 10, 11],
                  [12, 13, 14],
                  [15, 16, 17]]]], ms.float32)
    y = Tensor([[[[28, 29, 30],
                  [31, 32, 33]],
                 [[34, 35, 36],
                  [37, 38, 39]]]], ms.float32)
    net = Net(2, 0, -1, 1)
    output = net(x, y)
    expect_output = [[[[28., 29., 30.],
                       [31., 32., 33.],
                       [6., 7., 8.]],
                      [[34., 35., 36.],
                       [37., 38., 39.],
                       [15., 16., 17.]]]]
    assert np.allclose(output.asnumpy(), expect_output)


@arg_mark(plat_marks=['platform_ascend'], level_mark='level0', card_mark='onecard', essential_mark='essential')
@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
def test_ops_slice_scatter_neg_start(mode):
    """
    Feature: ops.slice_scatter
    Description: Verify the result of slice_scatter with neg start.
    Expectation: success
    """
    ms.set_context(mode=mode)
    x = ms.ops.zeros((4, 6), dtype=ms.int32)
    y = ms.ops.ones((4, 3), dtype=ms.int32)
    net = Net(1, -6, 5, 2)
    output = net(x, y)
    expect_output = [[1, 0, 1, 0, 1, 0],
                     [1, 0, 1, 0, 1, 0],
                     [1, 0, 1, 0, 1, 0],
                     [1, 0, 1, 0, 1, 0]]

    assert np.allclose(output.asnumpy(), expect_output)
